Recipe suggestion apparatus and method

ABSTRACT

A computer-implemented method is disclosed for suggesting recipes. Within the method, one or more point-of-sale transactions may be conducted. The transactions may involve a computer system and a customer possessing a mobile computing device. The computer system may store receipt data documenting the transactions. The computer system may also receive a request from the mobile computing device for one or more recipes, analyze the receipt data to identify at least one of the food patterns and food preferences of the customer, and identify one or more recipes corresponding to at least one of the food patterns and food preferences. The computer system may then pass the one or more recipes to the mobile computing device.

BACKGROUND

Field of the Invention

This invention relates to point-of-sale systems and more particularly tosystems and methods for analyzing electronic receipt data and suggestingrecipes relevant thereto.

Background of the Invention

Many point-of-sale (POS) systems currently in use today do not supportimportant emerging technologies, services, and marketing opportunities.For example, many POS systems are limited in their ability to collectand analyze electronic receipt data. As a result, those POS systemscannot effectively implement many novel methods and services surroundingsuch data. Accordingly, what is needed is an apparatus and methodexpanding the ability of a wide variety of POS systems and supportingcomputer systems, include legacy POS systems, to use electronic receiptdata to benefit customers.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the advantages of the invention will be readilyunderstood, a more particular description of the invention brieflydescribed above will be rendered by reference to specific embodimentsillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the invention and are not thereforeto be considered limiting of its scope, the invention will be describedand explained with additional specificity and detail through use of theaccompanying drawings, in which:

FIG. 1 is a schematic block diagram of one embodiment of a recipe inaccordance with the present invention;

FIG. 2 is a schematic block diagram of one embodiment of a point-of-sale(POS) system for implement methods in accordance with the presentinvention;

FIG. 3 is a schematic block diagram of one embodiment of multiple POSsystems in accordance with the present invention operating in thecontext of an enterprise-wide system;

FIG. 4 is a schematic block diagram of one embodiment of a receipt inaccordance with the present invention;

FIG. 5 is a schematic block diagram of one embodiment of a receiptmodule in accordance with the present invention;

FIG. 6 is a schematic block diagram of one embodiment of a recipe modulein accordance with the present invention; and

FIG. 7 is a block diagram of one embodiment of a method for suggestingone or more recipes in accordance with the present invention.

DETAILED DESCRIPTION

It will be readily understood that the components of the presentinvention, as generally described and illustrated in the Figures herein,could be arranged and designed in a wide variety of differentconfigurations. Thus, the following more detailed description of theembodiments of the invention, as represented in the Figures, is notintended to limit the scope of the invention, as claimed, but is merelyrepresentative of certain examples of presently contemplated embodimentsin accordance with the invention. The presently described embodimentswill be best understood by reference to the drawings, wherein like partsare designated by like numerals throughout.

Referring to FIG. 1, in selected embodiments, one or more computers,computers systems, mobile computing devices, or the like or acombination or sub-combination thereof may support, enable, oradminister a recipe-suggestion apparatus and/or method. A recipe 10 maybe defined as a collection of information 12 describing how to prepare aparticular culinary dish. By following a recipe 10, even aninexperienced preparer can repeatably produce a quality dish. As aresult, recipes 10 are particularly useful when a preparer would like toexpand his or her repertoire, add variety to his or her diet, or take ona new challenge.

Just as there is a substantially unlimited number of dishes, there isalso a substantially unlimited number of recipes 10. The challenge isoften not to find a recipe 10, but rather to find a user-friendly recipe10 describing how to prepare a quality dish that is relevant to one'stastes, preferences, skill level, and the like. Accordingly, selectedembodiments in accordance with the present invention may facilitate theprocess by working to find and present or suggest quality recipes thatare likely relevant to the corresponding individual. For example,certain embodiments may analyze a customer's receipt data to identifyone or more purchase patterns or cuisine preferences that may be used insuggesting a recipe relevant to the customer.

Selected embodiments in accordance with the present invention mayutilize one or more collections 14 of recipes 10. Such collections 14may be obtained in any suitable manner. For example, in selectedembodiments, a collection 14 may be developed, researched, and/orcompiled by a retailer (e.g., a retailer whose receipt data is beinganalyzed to assist in identifying relevant recipes) or an agent thereof.Alternatively, a collection 14 may be obtained (e.g., licensed) from athird party (e.g., a party independent from the retailer) such as areputable chef, culinary publisher, culinary school, or the like.

A collection 14, and the recipes 10 contained therein, may have anysuitable form. For example, selected embodiments may leverage acollection 14 of recipes 10 contained and indexed within a recipedatabase. The various recipes 10 contained within such a collection 14may comprise any suitable arrangement of preparation information 12 orother data. For example, in certain embodiments, each recipe 10 of acollection 14 may include a name 12 a of the dish, one or morephotographs 12 b of the dish at various stages of preparation and/or infinished form, a listing 12 c of required ingredients with correspondingquantities or proportions, preparation instructions 12 d or information12 d (e.g., a list of necessary equipment, a description of anenvironment needed to prepare the dish, a list of preparation steps, orthe like), other information 12 e (e.g., an indication of how much timeit will take to prepare the dish, a number of servings that the recipe10 will provide, nutritional information, etc.), or the like or acombination of sub-combination thereof.

Additionally, in selected embodiments, a recipe 10 may include metadata16. Metadata 16 may be described as “content about content.”Accordingly, in the context of a recipe 10, metadata 16 may compriseinformation about the recipe 10. For example, metadata 16 includedwithin a recipe 10 may be information characterizing an ethnic orgeographic origin or influence represented in a dish (e.g., type ofcuisine), whether the dish is spicy or mild, whether the dish is sweetor savory, or the like. Metadata 16 may also include informationregarding whether the dish is low in sodium, low in fat, low incarbohydrates, gluten free, vegetarian, strict vegetarian (e.g., vegan),or the like.

Embodiments in accordance with the present invention may be embodied asan apparatus, method, or computer program product. Accordingly, thepresent invention may take the form of an entirely hardware embodiment,an entirely software embodiment (including firmware, resident software,micro-code, etc.), or an embodiment combining software and hardwareaspects that may all generally be referred to herein as a “module” or“system.” Furthermore, the present invention may take the form of acomputer program product embodied in any tangible medium of expressionhaving computer-usable program code embodied in the medium.

Any combination of one or more computer-usable or computer-readablemedia may be utilized. For example, a computer-readable medium mayinclude one or more of a portable computer diskette, a hard disk, arandom access memory (RAM) device, a read-only memory (ROM) device, anerasable programmable read-only memory (EPROM or Flash memory) device, aportable compact disc read-only memory (CDROM), an optical storagedevice, and a magnetic storage device. In selected embodiments, acomputer-readable medium may comprise any non-transitory medium that cancontain, store, communicate, propagate, or transport the program for useby or in connection with the instruction execution system, apparatus, ordevice.

Computer program code for carrying out operations of the presentinvention may be written in any combination of one or more programminglanguages, including an object-oriented programming language such asJava, Smalltalk, C++, or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on acomputer of a point-of-sale (POS) system, partly on a POS computer, as astand-alone software package, on a stand-alone hardware unit, partly ona remote computer spaced some distance from the POS computer, orentirely on a remote computer or server. In the latter scenario, theremote computer may be connected to the POS computer through any type ofnetwork, including a local area network (LAN) or a wide area network(WAN), or the connection may be made to an external computer (e.g.,through the Internet using an Internet Service Provider).

Embodiments can also be implemented in cloud computing environments. Inthis description and the following claims, “cloud computing” is definedas a model for enabling ubiquitous, convenient, on-demand network accessto a shared pool of configurable computing resources (e.g., networks,servers, storage, applications, and services) that can be rapidlyprovisioned via virtualization and released with minimal managementeffort or service provider interaction, and then scaled accordingly. Acloud model can be composed of various characteristics (e.g., on-demandself-service, broad network access, resource pooling, rapid elasticity,measured service, etc.), service models (e.g., Software as a Service(“SaaS”), Platform as a Service (“PaaS”), Infrastructure as a Service(“IaaS”), and deployment models (e.g., private cloud, community cloud,public cloud, hybrid cloud, etc.).

The present invention is described below with reference to flowchartillustrations and/or block diagrams of methods, apparatus (systems) andcomputer program products according to embodiments of the invention. Itwill be understood that each block of the flowchart illustrations and/orblock diagrams, and combinations of blocks in the flowchartillustrations and/or block diagrams, can be implemented by computerprogram instructions or code. These computer program instructions may beprovided to a processor of a general purpose computer, special purposecomputer, or other programmable data processing apparatus to produce amachine, such that the instructions, which execute via the processor ofthe computer or other programmable data processing apparatus, createmeans for implementing the functions/acts specified in the flowchartand/or block diagram block or blocks.

These computer program instructions may also be stored in acomputer-readable medium that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablemedium produce an article of manufacture including instruction meanswhich implement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions which execute on the computer or other programmableapparatus provide processes for implementing the functions/actsspecified in the flowchart and/or block diagram block or blocks.

Referring to FIG. 2, in selected embodiments, the hardware, software, orhardware and software of a POS system 22 may be configured to implementone or more methods in accordance with the present invention. A POSsystem 22 in accordance with the present invention may include variouscomponents. In certain embodiments, a POS system 22 may include acentral or primary computer 24, a monitor 26 (e.g., a cashier-facingmonitor 26), one or more input devices 28 (e.g., scanners 28 a,keyboards 28 b, scales, or the like), one or more payment devices 30(e.g., cash drawers 30 a, card readers 30 b) for receiving or returningpayments, one or more output devices 32 (e.g., customer-facing display32 a or monitor 32 a, receipt printer 32 b), or the like or combinationsor sub-combinations thereof.

A computer 24 may form the primary processing unit of a POS system 22.Other components 28, 30, 32 forming part of a POS system 22 maycommunicate with the computer 24. Input devices 28 and certain paymentdevices 30 may feed data and commands to a computer 24 for processing orimplementation. For example, a scanner 28 a may pass data communicatingthe identity of one or more items to be purchased, returned, or the liketo a computer 24. Similarly, a card reader 30 b may pass paymentinformation to a computer 24.

Conversely, output devices 32 and certain payment devices 30 may followor implement commands issued by a computer 24. For example, a cashdrawer 30 a may open in accordance with the commands of a computer 24.Similarly, a customer-facing display 32 a and receipt printer 32 b maydisplay or output data or information as instructed by a computer 24.

In selected embodiments, in addition to handling consumer transactions(e.g., purchases, returns), a POS system 22 may also provide or supportcertain “back office” functionality. For example, a POS system 22 mayprovide or support inventory control, purchasing, receiving andtransferring products, or the like. A POS system 22 may also store salesand customer information for reporting purposes, marketing purposes,receivables management, trend analysis, cost analysis, price analysis,profit analysis, or the like. If desired or necessary, a POS system 22in accordance with the present invention may include an accountinginterface to pass certain information to one or more in-house orindependent accounting applications.

Referring to FIG. 3, in selected embodiments, a POS system 22 mayoperate substantially independently, as a stand-alone unit. Alternately,a POS system 22 in accordance with the present invention may be one ofseveral POS systems 22 forming the front line of a larger system. Forexample, multiple POS systems 22 may operate at a particular location 34(e.g., within a retail, brick-and-mortar store). In such embodiments,the various POS systems 22 may be interconnected via a LAN 36. A LAN 36may also connect the POS systems 22 to a local server 38.

A local server 38 may support the operation of the associated POSsystems 22. For example, a server 38 may provide a central repositoryfrom which certain data needed by the associated POS systems 22 may bestored, indexed, accessed, or the like. A server 38 may serve certainsoftware to one or more POS systems 22. In certain embodiments, a POSsystem 22 may offload certain tasks, computations, verifications, or thelike to a server 38.

Alternatively, or in addition thereto, a server 38 may support certainback office functionality. For example, a server 38 may receive andcompile (e.g., within one or more associated databases 40) data from thevarious associated POS systems 22 to provide or support inventorycontrol, purchasing, receiving and transferring products, or the like. Aserver 38 may also receive and compile sales and customer informationfor reporting purposes, marketing purposes, receivables management,trend analysis, cost analysis, price analysis, profit analysis, or thelike.

In certain embodiments, one or more POS systems 22 or servers 38corresponding to a particular location 34 may communicate with or accessone or more remote computers or resources via one or more networkdevices 42. For example, a network device 42 may enable a POS system 22to contact outside resources and verify the payment credentials (e.g.,credit card information) provided by a customer. A network device 42 maycomprise a modem, router, or the like.

In selected embodiments, a POS system 22 in accordance with the presentinvention may operate within an enterprise-wide system 44 comprisingmultiple locations 34 (e.g., branches 34 or stores 34). In suchembodiments, each location 34 may have one or more POS systems 22, localservers 38, local databases 40, network devices 42, or the like orcombinations or sub-combinations thereof connected by a computer network(e.g., a LAN 36). Additionally, each such location 34 may be configuredto interact with one or more supervisory systems 46. For example,multiple branch locations 34 may report to an associated “headquarters”location or system.

A supervisory system 46 may comprise one or more supervisory servers 48,databases 50, workstations 52, network devices 54, or the like orcombinations or sub-combinations thereof. The various components of asupervisory system 46 may be interconnected via a computer network(e.g., a LAN 56). In selected embodiments, a supervisory system 46 maycomprise one or more supervisory servers 48 providing a centralrepository from which certain data needed by the one or more POS systems22 or local servers 38 may be stored, indexed, accessed, or the like.

Alternatively, or in addition thereto, a supervisory server 48 mayreceive and compile (e.g., within one or more associated databases 50)data from the various associated POS systems 22 or local servers 38 toprovide or support inventory control, purchasing, receiving andtransferring products, or the like. A supervisory server 48 may alsoreceive and compile sales and customer information for reportingpurposes, marketing purposes, receivables management, trend analysis,cost analysis, price analysis, profit analysis, or the like.

A supervisory system 46 may be connected to one or more associatedlocations 34 or branches 34 in via any suitable computer network 58(e.g., WAN 58). For example, in selected embodiments, one or morelocations 34 may connect to a supervisor system 46 via the Internet.Communication over such a network 58 may follow any suitable protocol orsecurity scheme. For example, communication may utilize the FileTransfer Protocol (FTP), a virtual private network (VPN), intranet, orthe like.

Referring to FIG. 4, a POS system 22 may collect and/or generate receiptdata 60. Receipt data 60 may document a transaction (e.g., sale orreturn) carried out by a POS system 22. Receipt data 60 may be presentedor displayed to a customer in the form of an electronic (e.g.,paperless) receipt 62. In selected embodiments, receipt data 60 may bedelivered to a customer's computing device (e.g., a mobile telephone,personal digital assistant (PDA), media player, tablet computer orreader, laptop computer, desktop computer, or the like, hereinafter a“computing device”) by an entity's computer system (e.g., a systemcomprising one or more POS systems 22, local servers 38, supervisoryservers 48, some other onsite resources, one or more applicationsrunning on a customer's computing device, some other offsite resources,or the like or combinations or sub-combinations thereof, hereinafter a“computer system”).

In selected embodiments, receipt data 60 and an electronic receipt 62may include a logo 64, contact information 66, a list 68 of itemspurchased or returned, a total 70 indicating the sales tax assessed orreturned, a total 72 indicating the amount paid or returned, paymentinformation 74, other information 76, or the like or combinations orsub-combinations thereof.

A logo 64 may reinforce the brand and image of the associated entitywithin the mind of a consumer. By including contact information 66 on anelectronic receipt 62, an entity may ensure that a customer has readyaccess to one or more physical addresses, Internet address, telephonenumbers, facsimile numbers, hours of operation, or the like orcombinations or sub-combinations thereof. One or more of a list 68 ofitems purchased or returned, a total 70 indicating the sales taxassessed or returned, a total 72 indicating the amount paid or returned,and payment information 74 (e.g., date of transaction, an indication ofmethod of payment, an indication of which credit or debit card was used,etc.) may be included to document important details of a transaction.

Other information 76 may be included within an electronic receipt 62 asdesired or necessary. For example, to promote brand loyalty, an entitymay include an indication of an amount saved in the transaction, ayearly total of the amount saved, reward points earned, or the like.Alternatively, or in addition thereto, other information 60 may includepromotional information, a solicitation to participate in a survey, anemployment opportunity, contest information, or the like.

An electronic receipt 62 may be presented by a computing device of acustomer in any suitable layout or format. For example, the receipt data60 forming an electronic receipt 62 may simply be presented as a textuallist. Alternatively, an electronic receipt 62 may follow the form of apaper receipt. That is, the electronic receipt 62 may comprise a virtualrepresentation or layout substantially matching what a comparable paperreceipt would look like.

The manner in which an electronic receipt 62 is presented or displayedon a computing device of a customer may be completely dictated by thecomputer system delivering the receipt data 60 thereto. Alternatively,the computing device of the customer may have an application (e.g., areceipt manager, accounting program, budgeting program, or the like)installed thereon. Such an application may partially or completelycontrol the layout or format of an electronic receipt 62 displayedtherewith or therethrough. For example, a computer system may supplyreceipt data 60, while the application installed on the computing deviceof the customer supplies the layout or formatting.

Referring to FIG. 5, a computer system in accordance with the presentinvention may deliver receipt data 60 to a computing device of acustomer in any suitable manner. In selected embodiments, a receiptmodule 78 may enable or support such delivery. A receipt module 78 mayinclude any suitable arrangement of sub-components or modules. Incertain embodiments, a receipt module 78 may include an image module 80,identification module 82, notification module 84, synchronization module86, one or more other modules 88 as desired or necessary, or the like orsome combination or sub-combination thereof.

An image module 80 may assemble, generate, or obtain an advertisementcomprising a call to action. A call to action may invite or motivate acustomer to take a particular step or action. For example, a call toaction may invite or motive a consumer to download receipt data 60. Toincrease the likelihood that a consumer will respond favorably to thecall to action, an advertisement may include an enabler facilitating thedesired step or action. For example, in selected embodiments, anadvertisement may include a machine-readable code. By scanning the code(e.g., scanning the code using a camera on a mobile telephone, tabletcomputer, or the like), a consumer may import receipt data 60 encodedwithin the code. Alternatively, scanning the code may initiate thedownload of receipt data 60.

For example, a machine-readable code may be encoded with a URL. Inaddition to designating a particular resource, a URL may also include atransaction identification (ID). Accordingly, after an appropriateapplication is launched and a machine-readable code is scanned, a URLmay be passed from a customer (e.g., from a mobile telephone of acustomer) to an Internet Service Provider (e.g., a telecommunicationsprovider). As a result, an appropriate resource within a computer systemmay be accessed and receipt data may be returned to (e.g., downloadedby) a computing device.

In selected embodiments, a machine-readable code may comprise a barcode.For example, in certain embodiments, a machine-readable code maycomprise a two-dimensional barcode. Two-dimensional barcodes may supportor provide more data per unit area than can be obtained using atraditional one-dimensional barcode. Moreover, two-dimensional barcodesare typically configured to be scanned using a camera, an item that iscommonly found on personal electronic devices. A two-dimensional barcodefor use in accordance with the present invention may follow any suitableprotocol, format, or system. In selected embodiments, a two-dimensionalcode may be embodied as a Quick Response (QR) Code.

An identification module 82 may be tasked with requesting, collecting,and/or communicating identification information linking a customerassociated with a transaction with one or more records stored within acomputer system. For example, as part of a transaction carried out at aPOS system 22, an identification module 82 may request, collect, and/orcommunicate identification information linking a transaction to aparticular computing device corresponding to the customer participatingin the transaction. Thus, information corresponding to the transactionmay be passed to the customer via the particular computing device.

An identification module 82 may request, collect, and/or communicate oneor more types of identification information. For example, in selectedembodiments, an identification module 82 may collect a uniqueidentification or membership number from a customer. This may be donewhen a membership card, club card, loyalty card, identification card,credit card, debit card, fingerprint or other biometric characteristic,or the like is scanned, input, or otherwise collected at a POS system22. In other situations, a cashier or customer may type in a uniqueidentification number, payment number, membership number, or the like ata POS system 22. For example, while a cashier is processing atransaction, a customer may be prompted via a card reader 30 b,customer-facing display 32 a, or the like to enter (e.g., type in usingthe card reader 30 b) a mobile telephone number corresponding to thecustomer. Alternatively, a cashier may type in a telephone numbercorresponding to the customer.

Once the identification information is received, it may be used directly(e.g., used directly to pass receipt data 60 to a computing device of acorresponding customer). Alternatively, or in addition thereto, theidentification information may tie or link a current transaction to oneor more previously stored computer records. For example, within suchrecords, a computer system may find the information necessary toidentify and communicate with a computing device or account of acorresponding customer. Alternatively, or in addition thereto, suchrecords may enable a computer system to tie or link a currenttransaction to an appropriate computing device or account.

A notification module 84 may assemble, generate, obtain, direct, and/orissue one or more push notifications. In selected embodiments, pushnotifications may be directed to a computing device of a customer. Forexample, when an appropriate application in not running on a computingdevice, push notifications may inform the customer that certain data oroptions are available (e.g., that a new electronic receipt 62 isavailable for download).

A synchronization module 86 may support or enable one way or two waydata communication between a computer system and a computing device. Forexample, a synchronization module 86 may support or enable the passingof receipt data 60 from a computer system to a computing device. Asynchronization module 86 may also enable certain data received from acomputing device to be incorporated within or used by a computer system.For example, one or more user preferences (e.g., notificationpreferences) may be communicated to a computer system from anapplication resident on a computing device.

The various functions or modules of a receipt module 78 may be enactedor implemented by any suitable system or component thereof. For example,in selected embodiments, one or more functions or modules of a receiptmodule 78 may be distributed across one or more hardware devices,including a primary computer 24 of a POS system 22, a local server 38, asupervisory server 48, some other onsite resource, a computing device,some other offsite resource, or the like or combinations orsub-combinations thereof. Thus, systems and methods in accordance withthe present invention may be adapted to a wide variety of situations,including more rigid legacy systems.

Referring to FIG. 6, in selected embodiments, one or more computers,computers systems, mobile computing devices, or the like or acombination or sub-combination thereof may support or enable a recipemodule 90. A recipe module 90 may enable certain receipt data 60 to beused when suggesting one or more recipes 10 to a corresponding customer.A recipe module 90 may include any suitable arrangement ofsub-components or modules. In certain embodiments, a recipe module 90may include a data store 92, analysis module 94, output module 96,conversion module 98 one or more other modules 100 as desired ornecessary, or the like or a combination or sub-combination thereof.

A data store 92 may contain records supporting the operation of a recipemodule 90. In selected embodiments, a data store 92 may contain one ormore recipes 10. For example, a data store 92 may store one or morerecipe databases 102, each of which may contain one or more collections14 of recipes 10. Accordingly, a recipe module 90 may utilize or accessa plurality of recipes 10 stored in electronic format.

An analysis module 94 may be programmed to analyze receipt data 60corresponding to one or more customers in order to identify one or morerecipes 10 contained in a data store 92 that are likely to be relevantto those customers. An analysis module 94 may perform such analysis andidentifications in any suitable manner.

In selected embodiments, an analysis module 94 may analyze receipt data60 to identify purchase patterns, cuisine preferences, or the like orcombinations thereof. Purchase patterns may provide a “micro” ordetailed view of the food products or items purchased. Cuisinepreferences, on the other hand, may provide a “macro” or high level viewof the types of food or cuisines preferred by a particular customer.Accordingly, an analysis module 94 may perform micro and/or macroanalysis of receipt data 60

For example, in certain embodiments, receipt data 60 may be analyzed byan analysis module 94 at substantially exclusively the micro level toidentify purchasing patterns. Once a purchasing pattern has beenidentified, it may be used in identifying one or more recipes 10 thatcorrespond to the pattern. For example, by analyzing receipt data 60, ananalysis module 94 may identify a purchase pattern wherein a particularcustomer purchases a statistically significant amount of pasta.Accordingly, an analysis module 95 may identify one or more recipes 10that correspond at the micro level (e.g., call for pasta).

Alternatively, receipt data 60 may be analyzed at both the micro andmacro levels. For example, receipt data 60 may be analyzed at a microlevel in order to assign or determine one or more macro levelcharacterizations. That is, certain products or items may correlate toparticular cuisines. Pasta, for example, is closely associated withItalian cuisine. Accordingly, a purchase pattern wherein a particularcustomer purchases a statistically significant amount of pasta may beused as a micro level indicator of a macro level preference for Italiancuisine. An analysis module 94 may, therefore, identify one or morerecipes 10 that correspond at the macro level (e.g., are directed toItalian cuisine).

Any suitable granularity or resolution may be applied or used by ananalysis module 94 when identifying, selecting, or assigning microand/or macro characterizations. In selected embodiments, the granularityor resolution may correspond to, follow, or match an ability of ananalysis module 94 to resolve such differences. For example, in selectedembodiments, certain macro preferences may simply be characterized as“Asian,” “Italian”, “Mexican,” or the like. Alternatively, an analysismodule 94 may differentiate to a higher degree (e.g., between a Chinesemacro preference and one or more other Asian macro preferences orbetween a macro preference for Szechuan cuisine and one or more otherregional cuisines within China).

Statistical significance may be determined in any suitable manner. Inselected embodiments, statistical significance may correspond to themere presence of a particular product or set of products within thereceipt data 60. For example, the mere presence of a gluten-free floursubstitute within receipt data 60 may justify an analysis module 94 inassociating a macro level characterization of “gluten free” to thecorresponding customer. Accordingly, the analysis module 94 may identifyone or more recipes 10 that are gluten free.

Alternatively, or in addition thereto, statistical significance maycorrespond to one or more numeric characterizations. In selectedembodiments, statistical significance may correspond to meeting,passing, or falling below a particular numeric threshold. For example,one or more purchases of a particular product or set of products may bestatistically significant if they are greater than, equal to, or lessthan a particular percentage by weight and/or cost of one or morepurchases.

For example, the purchase of ground beef may be statisticallysignificant if, over some number of shopping trips, the amount spent onground beef is greater than or equal to some percentage (e.g., 7%) ofthe total amount spent on food in those trips. When such is the case, ananalysis module 94 may be programmed to select or assign a micro levelcharacterization associated with ground beef to the correspondingcustomer. Accordingly, the analysis module 94 may identify one or morerecipes 10 that are call for ground beef.

In another example, the absence of meat, milk, eggs, or otheranimal-derived products may be statistically significant if, over somenumber of shopping trips, the amount spent on such items is less thansome percentage (e.g., 3%, 1%, or the like) of the total amount spent onfood in those trips. When such is the case, an analysis module 94 may beprogrammed to select or assign a macro level characterization associatedwith vegetarianism, strict vegetarianism, veganism, or the like to thecorresponding customer. Accordingly, the analysis module 94 may identifyone or more recipes 10 that are vegetarian, strictly vegetarian, vegan,or the like.

In analyzing receipt data 60, an analysis module 94 may identify,select, or assign more than one characterization to a particularcustomer. For example, an analysis module 94 may identify and assign amicro level pattern associated with chicken as well as a macro levelpreference for Italian cuisine to a customer. Accordingly, inidentifying one or more recipes 10 for the customer, an analysis module94 may identify recipes 10 corresponding to the micro pattern (e.g., arecipe 10 for Chicken Cordon Bleu), macro preference (e.g., a recipe 10for pasta primavera), or both the micro pattern and macro preference(e.g., a recipe 10 for chicken parmigiana).

In certain embodiments, an analysis module 94 may apply a methodologysomewhat different from that described hereinabove. Accordingly, inselected embodiments, an analysis module 94 may utilize a less heuristicapproach. For example, an analysis module 94 may use a full receipthistory (e.g., a complete collection of receipt data 60 corresponding toa particular customer) as a training set or model that may be used tofind new (e.g., other) food product or products the correspondingcustomer should like. The analysis module 94 may then find recipes 10that contain the new food product or products. Thus, an analysis module94 may use product recommendation techniques, then find the recipes 10that contain the new products.

In selected embodiments, an analysis module 94 may include a controlmodule 104. A control module 104 may provide a mechanism through which acustomer may express his or her desire to see one or more suggestedrecipes 10. A control module 104 may also grant one or more customerssome level of control over the recipes 10 identified by an analysismodule 94 in their behalf. For example, a control module 104 may enablea customer to establish a black list, white list, or the like withrespect to certain ingredients, dishes, cuisines (e.g., vegetarian,vegan), nutritional characteristics (e.g., low in sodium, low in fat),required skills or experience, or the like. An analysis module 94 maythen consider and respect such inputs or preferences when identifyingrecipes 10.

In certain embodiments, a control module 104 may enable one or morecustomers to set, input, or otherwise communicate an experimentationsetting. An experimentation setting may be a measure of how differentone or more recipes 10 are from the purchase patterns and/or foodpreferences of a customer. In many situations, a customer may desirethat an analysis module 94 identify recipes 10 that are closelyassociated with his or her purchase patterns or food preferences.However, in other situations, a customer may want to experiencesomething new. Accordingly, this desire may be communicated via acontrol module 104.

For example, in selected embodiments, a control module 104 may present a“Try Something New” or “Surprise Me” bottom. Alternatively, a controlmodule 104 may present a scale (e.g., a slider or the like). A firstextreme of the scale may correspond to a tight correlation betweenpurchase patterns, cuisine preferences, and recipes 10. A second,opposite extreme of the scale may correspond to a loose correlation(e.g., an opposite correlation, a cross correlation, or the like)between purchase patterns, cuisine preferences, and recipes 10.Accordingly, by selecting an appropriate location on the scale, acustomer may communicate additional information that may be used by ananalysis module 94 to identify relevant recipes 10.

For example, based on an experimentation setting proximate a firstextreme, an analysis module 94 may identify one or more recipes 10closely associated with the micro patterns and/or macro preferences ofthe corresponding customer. Based on an intermediate experimentationsetting, an analysis module 94 may identify one or more recipes 10 lessassociated with the micro patterns and/or macro preferences of thecorresponding customer. For example, an analysis module 94 may identifyrecipes 10 corresponding to certain macro preferences (e.g., apreference for Italian cuisine), but not certain micro patterns (e.g.,disregarding a pattern of consuming chicken).

Alternatively, based on an experimentation setting proximate a secondextreme, an analysis module 94 may identify one or more recipes 10 evenless associated with the micro patterns and/or macro preferences of thecorresponding customer. For example, an analysis module 94 may identifyrecipes 10 corresponding to certain micro preferences, but not certainmacro patterns. Thus, if a customer has a micro pattern of purchasingbeef and a macro preference for Italian cuisine, an analysis module 94may identify one or more recipes 10 that contain beef, but do notcorrespond to Italian cuisine (e.g., that relate to Chinese cuisine). Insuch embodiments or situations, the commonality in a core ingredient mayincrease the likelihood that the customer will enjoy the correspondingdish, while the differences in cuisine may satisfy the customer's desireto try something new or out of the ordinary.

An output module 96 may support or enable the passing and presentationof one or more recipes 10 to appropriate customers. In passing andpresenting recipes 10, an output module 96 may rely on the recordscontained with a data store 92. In selected embodiments or situations,an output module 96 may pass or present more than one recipe 10 to thevarious customers. Accordingly, a customer may scroll, swipe, pan, orotherwise progress through an array of potentially relevant recipes 10.

In selected embodiments or situations, a customer may desire to use aparticular recipe 10 identified by an analysis module 94 and deliveredby an output module 96. Such a desire may be accompanied by a need toshop for one or more of the ingredients associated with the recipe 10.Accordingly, the customers may desire to generate or modify a shoppinglist based on the recipe 10.

In certain embodiments, a recipe 10 may be tightly integrated with theproducts offered for sale by a particular retailer. Such recipes 10 maybe considered to be product-specific. That is, the receipts 10 may referor cite directly to one or more specific products sold by the particularretailer. Accordingly, a shopping list may be generated or modifieddirectly from such recipes 10.

Alternatively, a recipe 10 may originate with an entity independent ofany retailer or any products offered thereby. Such recipes 10 may beconsidered to be product-independent. That is, the receipts 10 may notrefer or cite directly to one or more specific products sold by theparticular retailer. A shopping list may not be generated or modifieddirectly from such recipes 10. Accordingly, in selected embodiments, arecipe module 90 may include a conversion module 96 to convert one ormore product-independent recipes 10 into one or more correspondingshopping lists, use one or more product-independent recipes 10 to modifyan existing shopping list, and/or convert one or moreproduct-independent recipes 10 into product-specific recipes 10.

In certain embodiments, a conversion module 98 may use fuzzy logic orthe like to correlate one or more recited ingredients to one or morecorresponding products sold by a particular retailer. For example, arecipe 10 may recite “½ cup sliced almonds.” Comparing this recitationto certain products known to be sold by a particular retailer, aconversion module 98 may identify one or more suitable products. Forexample, a conversion module 98 may identify “DIAMOND Almonds, Sliced,6-Ounce Bag.” Accordingly, a conversion module 98 may cite the DIAMONDproduct in a corresponding shopping list or product-specific recipe 10.

The various functions or modules of a recipe module 90 may be enacted orimplemented by any suitable system or component thereof. For example, inselected embodiments, one or more functions or modules of a recipemodule 90 may be distributed across one or more hardware devices,including a primary computer 24 of a POS system 22, a local server 38, asupervisory server 48, some other onsite resource, a computing device,some other offsite resource, or the like or combinations orsub-combinations thereof. Thus, systems and methods in accordance withthe present invention may be adapted to a wide variety of situations,including more rigid legacy systems.

Referring to FIG. 7, one method 106 in accordance with the presentinvention may begin when an appropriate application (e.g., a retailer'smobile application, an electronic receipts application, or the like or acombination or sub-combination thereof) is issued 108 and installed on acomputing device of a customer. A computer system may then enroll 110the customer in an electronic receipts program. In selected embodiments,this enrollment 110 may result in the computing device being linked toor associated with certain identification information within the recordsof a computer system.

So prepared, a customer may then enter a “brick-and-mortar” businesslocation (e.g., enter a brick-and-mortar retail store with his or hercomputing device), select one or more items for purchase, and approach aPOS system 22. At the POS system 22, a transaction (e.g., a purchase ofone or more items) may be completed.

During the transaction, a computer system may receive identificationinformation. For example, a POS system 22 may scan a membership card,club card, loyalty card, identification card, credit card, debit card,or the like. From the scan, identification information (e.g., a uniqueidentification number, membership number, or the like) may be obtained.Alternatively, while a cashier is processing a transaction, a customermay be prompted via a card reader 32 b, customer-facing display 32 a, orthe like to enter (e.g., type in using the card reader 32 b) anidentification number (e.g., a mobile telephone number).

Identification information may be passed from a POS system 22 to one ormore other computers (e.g., servers 38, 48) within a computer system.The identification information may link a customer and a correspondingtransaction to one or more records stored within a computer system. Inselected embodiments, such records may contain the information necessaryto identify and communicate with a computing device of the correspondingcustomer. Accordingly, a computer system may deliver receipt data 60documenting the transaction to an appropriate computing device. In sucha manner, one or more transactions may be completed 112.

At some point thereafter, a computer system may receive 114 (e.g., froma customer via an application running on the customer's computingdevice) a request for one or more suggested recipes 10. Accordingly, acomputer system may analyze 116 the appropriate purchase history (e.g.,receipt data 60 collected in one or more completed 112 transactionsinvolving the corresponding customer), identify 118 one or more recipes10 that are potentially relevant to the customer, and present 120 (e.g.,via an application running on the customer's computing device) the oneor more recipes 10 to the customer.

In selected embodiments, the one or more recipes 10 may be presented oneat a time to the customer. For example, a first recipe 10 may bedisplayed or presented 120 first. In certain embodiments, a first recipe10 may be the recipe 10 deemed most likely to be relevant to thecustomer. Should the customer wish to advance to another recipe 10, heor she may so indicate via an appropriate user interface. A secondrecipe 10 may then be presented 120. In selected embodiments, the secondrecipe 10 may match the projected relevance of the first recipe 10 orhave a projected relevance less than that of the first recipe 10. Such aprogression through the recipes 10 may continue until the customer findsa recipe 10 he or she would like to try, the database 102 or databases102 of recipes 10 has been exhausted, or the customer abandons thesearch.

Should a customer elect to abandon a search, the method 106 may simplyend. Alternatively, should a customer locate a recipe 10 he or she wouldlike to try, the customer may so indicate by saving 122, selecting,bookmarking, or otherwise designating the recipe 10. Accordingly, thecustomer may easily refer to the recipe 10 in a future shopping trip,cooking event, or the like.

Once a customer has saved 122 or otherwise designating the appropriaterecipe 10, the method 106 may end. Alternatively, in selectedembodiments, a customer may wish to generate or modify a shopping listbased on the selected recipe 10. Accordingly, a computer system mayreceive 124 (e.g., from a customer via an application running on thecustomer's computing device) a request to convert the selected recipe10. The computer system may then identify 126 specific,commercially-available products corresponding to the ingredients listedin the recipe 10 and present 128 the identified products in the form anew or modified shopping list and/or product-specific recipe 10.

In selected embodiments, an analysis module 94 may learn from theinterplay of a customer with one or more suggested recipes 10. Forexample, an analysis module 94 may note which recipes 10 received themost attention from, or were selected by, a customer. Accordingly, ananalysis module 94 may analyze those recipes 10 to determine in anyidentifiable information, patterns, or preferences corresponding to thecustomer may be gleaned therefrom. Additionally, an analysis module 94may analyze future receipt data 60 in an effort to determine whether acustomer acted on a particular recipe 10. Thus, an analysis module 94may monitor and improve its own performance.

The flowchart in FIG. 7 illustrates the architecture, functionality, andoperation of possible implementations of systems, methods, and computerprogram products according to certain embodiments of the presentinvention. In this regard, each block in the flowchart may represent amodule, segment, or portion of code, which comprises one or moreexecutable instructions for implementing the specified logicalfunction(s). It will also be noted that each block of the flowchartillustration, and combinations of blocks in the flowchart illustration,may be implemented by special purpose hardware-based systems thatperform the specified functions or acts, or combinations of specialpurpose hardware and computer instructions.

It should also be noted that, in some alternative implementations, thefunctions noted in the blocks may occur out of the order noted in theFigure. In certain embodiments, two blocks shown in succession may, infact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. For example, in selected embodiments, the stepor steps of analyzing 116 purchase history and/or identifying 118recipes may occur before a request for suggest recipes 10 is received114. Alternatively, certain steps or functions may be omitted if notneeded.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrative,and not restrictive. The scope of the invention is, therefore, indicatedby the appended claims, rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

What is claimed is:
 1. A method for suggesting recipes, the methodcomprising: providing a first computer system having an input device;providing a second computer system in communication with the firstcomputer system, the second computer system having a processor includingan output module, an analysis module, and a control module; providing arecipe database that stores a plurality of recipes; receiving, throughthe first computer system, a plurality of sale transactions; forwardingthe plurality of sale transactions to the output module; generating,through the analysis module, a user interface control, the userinterface control representing a correlation scale ofcustomer-adjustable experimentation settings, the correlation scaleindicating the correlation of a recipe with each of a plurality of micropatterns and macro preferences of a customer, the micro patterns of thecustomer including sale transaction patterns for the customer, the macropreferences of the customer including categorized food types for thecustomer determined through analysis of the micro patterns; providing anapplication executable by a mobile computing device in communicationwith the second computer system; presenting, through the output module,the user interface control to the application, the user interfacecontrol representing the correlation scale, the correlation scaleembodied as a slidable scale with each position on the slidable scalerepresenting a different experimentation setting for the customer;receiving, through the control module, a selection of one of theexperimentation settings by the customer selecting one of the positionson the slidable scale; receiving, through the control module, a requestfor one or more recipes from the mobile computing device; analyzing,through the analysis module, the one or more sale transactions of thecustomer to identify each of the micro patterns of the customer andmacro preferences of the customer; identifying a food item within theone or more sale transactions; determining, through the analysis module,a statistical significance of the food item with respect to the one ormore sale transactions; correlating, by the analysis module, the fooditem with at least one of the micro patterns or at least one of themacro preferences of the customer upon a determination that thestatistical significance of the food item exceeds a predeterminedthreshold; omitting, by the analysis module, the food item from the oneor more micro patterns and the one or more macro preferences upon adetermination that the statistical significance of the food item doesnot exceed the predetermined threshold; indicating, through the analysismodule, a correlation between a recipe and each of the micro patterns ofthe customer and macro preferences of the customer for the recipe to beidentified as potentially relevant to the customer; identifying, throughthe analysis module, one or more of the plurality of recipes from withinthe recipe database as being potentially relevant to the customer, eachof the one or more recipes corresponding to the correlation a recipe isto have with each of: micro patterns of the customer, macro preferencesof the customer, and the customer-selected experimentation setting;associating at least one photograph with the one or more identifiedrecipes; and transmitting, through the output module, the one or moreidentified recipes and the at least one associated photograph to themobile computing device.
 2. The method of claim 1, wherein the firstcomputer system comprises a plurality of first computer systems housedwithin one or more retail, brick-and-mortar stores corresponding to aretailer.
 3. The method of claim 2, further comprising conducting theone or more sale transactions at one or more first computer systems ofthe plurality of first computer systems.
 4. The method of claim 3,wherein the one or more recipes are product-specific recipes.
 5. Themethod of claim 3, wherein the one or more recipes areproduct-independent recipes.
 6. The method of claim 5, furthercomprising obtaining the recipe database from an entity independent ofthe retailer.
 7. The method of claim 5, further comprising receiving,through a synchronization module within the processor, a request fromthe mobile computing device to convert a first recipe of the one or morerecipes into a product-specific recipe.
 8. The method of claim 7,further comprising applying, through the conversion module, fuzzy logicto the first recipe and converting, through the conversion module, thefirst recipe into a product-specific recipe.
 9. The method of claim 8,further comprising passing, through the output module, theproduct-specific recipe to the mobile computing device in the form of ashopping list or a modification to a shopping list.
 10. The method ofclaim 1, wherein identifying one or more recipes from within the recipedatabase comprises identifying one or more recipes corresponding to boththe purchase patterns and cuisine preferences.
 11. The method of claim1, wherein the identifying one or more recipes from within a recipedatabase comprises identifying one or more recipes corresponding tocuisine preferences that do not correspond to the purchase patterns. 12.A computer program product for use with a first computer system and asecond computer system in communication with the first computer systemconfigured for implementing a method for suggesting recipes, the firstcomputer having an input device and the second computer having aprocessor, the computer program product comprising: one or more computerstorage devices having stored thereon computer-executable instructionsthat, when executed on the processor including a control module, ananalysis module, and an output module, cause the processor to perform amethod including the following: storing a plurality of recipes in arecipe database; receiving, through the first computer system, aplurality of sale transactions; forwarding the plurality of saletransactions to the output module; generating, through the analysismodule, a user interface control, the user interface controlrepresenting a correlation scale of customer-adjustable experimentationsettings, the correlation scale indicating the correlation of a recipewith each of a plurality of micro patterns and macro preferences of acustomer, the micro patterns of the customer including sale transactionpatterns for the customer, the macro preferences of the customerincluding categorized food types for the customer determined throughanalysis of the micro, food items in the micro patterns having beenanalyzed to determine the macro preferences; providing an applicationexecutable by a mobile computing device in communication with the secondcomputer system; presenting, through the output module, the userinterface control to the application, the user interface controlrepresenting the correlation scale, the correlation scale embodied as aslidable scale with each position on the slidable scale representing adifferent experimentation setting for the customer; receiving, throughthe control module, a selection of one of the experimentation settingsby the customer selecting one of the positions on the slidable scale;receiving, through the control module, a request for one or more recipesfrom the mobile computing device; analyzing, through the analysismodule, receipt data for one or more point-of-sale transactions of thecustomer to identify each of: micro patterns of the customer and macropreferences of the customer, the macro preferences of the customerincluding categorized food types for the customer determined throughanalysis of the micro patterns; identifying a food item within one ormore of the sale transactions; determining, through the analysis module,a statistical significance of the food item with respect to the one ormore sale transactions; correlating, by the analysis module, the fooditem with at least one of the micro patterns or at least one of themacro preferences of the customer upon a determination that thestatistical significance of the food item exceeds a predeterminedthreshold; omitting, by the analysis module, the food item from the oneor more micro patterns and the one or more macro preferences upon adetermination that the statistical significance of the food item doesnot exceed the predetermined threshold; indicating, through the analysismodule, a correlation a recipe is to have with each of: micro patternsof the customer and macro preferences of the customer for the recipe tobe identified as potentially relevant to the customer; identifying,through the analysis module, one or more recipes from within a recipedatabase as being potentially relevant to the customer, each of the oneor more recipes corresponding to the correlation a recipe is to havewith each of: micro patterns of the customer, macro preferences of thecustomer, and the customer-selected experimentation setting; associatingat least one photograph with the one or more identified recipes; andtransmitting, through the output module, the one or more identifiedrecipes and the at least one associated photograph to the mobilecomputing device.
 13. The computer program product of claim 12, whereinthe first computer system comprises a plurality of first computersystems housed within one or more retail, brick-and-mortar storescorresponding to a retailer.
 14. The computer program product of claim13, further comprising computer-executable instructions that, whenexecuted, cause the mobile device to conduct the one or more saletransactions at one or more first computer systems of the plurality offirst computer systems.
 15. A system comprising: a first computer systemconfigured to receive a plurality of sale transactions and forward themto a second computer system; the second computer system, including: oneor more processors; system memory; an input device; a recipe databasefor storing a plurality of recipes; and one or more computer storagedevices having stored thereon computer-executable instructionsrepresenting a recipe module including a control module, an analysismodule, an output module, the recipe module configured to: generate,through the analysis module, a user interface control, the userinterface control representing a correlation scale ofcustomer-adjustable experimentation settings, the correlation scaleindicating the correlation of a recipe with each of a plurality of micropatterns and macro preferences of a customer, the micro patterns of thecustomer including sale transaction patterns for the customer, the macropreferences of the customer including categorized food types for thecustomer determined through analysis of the micro patterns; provide anapplication executable by a mobile computing device in communicationwith the second computer system; present, through the output module, theuser interface control to the application, the user interface controlrepresenting the correlation scale, the correlation scale embodied as aslidable scale with each position on the slidable scale representing adifferent experimentation setting for the customer; receive, through thecontrol module, selection of one of the experimentation settings by thecustomer selecting one of the positions on the slidable scale;receiving, through the control module, a request for one or more recipesfrom the mobile computing device in communication with the secondcomputer system; analyze, through the analysis module, receipt data forone or more point-of-sale transactions of the customer to identify eachof the micro patterns of the customer and macro preferences of thecustomer; identify a food item within one or more of the saletransactions; determine, through the analysis module, a statisticalsignificance of the food item with respect to the one or more saletransactions; correlate, by the analysis module, the food item with atleast one of the micro patterns or at least one of the macro preferencesof the customer upon a determination that the statistical significanceof the food item exceeds a predetermined threshold; omit, by theanalysis module, the food item from the one or more micro patterns andthe one or more macro preferences upon a determination that thestatistical significance of the food item does not exceed thepredetermined threshold; indicate, through the analysis module, acorrelation between a recipe and each of the micro patterns of thecustomer and macro preferences of the customer for the recipe to beidentified as potentially relevant to the customer; identify, throughthe analysis module, one or more of the plurality of recipes from withinthe recipe database as being potentially relevant to the customer, eachof the one the one or more recipes corresponding to the correlation arecipe is to have with each of: micro patterns of the customer, macropreferences of the customer, and the customer-selected experimentationsetting; associate at least one photograph with the one or moreidentified recipes; and transmit, through the output module, the one ormore identified recipes and the at least one associated photograph tothe mobile computing device.
 16. The system of claim 15, furthercomprising a plurality of first computer systems housed within one ormore retail, brick-and-mortar stores corresponding to a retailer. 17.The system of claim 15, wherein the system is further configured toreceive the receipt data from the one or more sale transactionsconducted at one or more first computer systems of the plurality offirst computer systems.